IAD: Indirect Anomalous VMMs Detection in the Cloud-Based Environment

Anshul Jindal, Ilya Shakhat, Jorge Cardoso, Michael Gerndt, Vladimir Podolskiy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Server virtualization in the form of virtual machines (VMs) with the use of a hypervisor or a Virtual Machine Monitor (VMM) is an essential part of cloud computing technology to provide infrastructure-as-a-service (IaaS). A fault or an anomaly in the VMM can propagate to the VMs hosted on it and ultimately affect the availability and reliability of the applications running on those VMs. Therefore, identifying and eventually resolving it quickly is highly important. However, anomalous VMM detection is a challenge in the cloud environment since the user does not have access to the VMM. This paper addresses this challenge of anomalous VMM detection in the cloud-based environment without having any knowledge or data from VMM by introducing a novel machine learning-based algorithm called IAD: Indirect Anomalous VMMs Detection. This algorithm solely uses the VM’s resources utilization data hosted on those VMMs for the anomalous VMMs detection. The developed algorithm’s accuracy was tested on four datasets comprising the synthetic and real and compared against four other popular algorithms, which can also be used to the described problem. It was found that the proposed IAD algorithm has an average F1-score of 83.7% averaged across four datasets, and also outperforms other algorithms by an average F1-score of 11%.

Original languageEnglish
Title of host publicationService-Oriented Computing – ICSOC 2021 Workshops - AIOps, STRAPS, AI-PA and Satellite Events, Proceedings
EditorsHakim Hacid, Monther Aldwairi, Mohamed Reda Bouadjenek, Marinella Petrocchi, Noura Faci, Fatma Outay, Amin Beheshti, Lauritz Thamsen, Hai Dong
PublisherSpringer Science and Business Media Deutschland GmbH
Pages190-201
Number of pages12
ISBN (Print)9783031141348
DOIs
StatePublished - 2022
EventInternational Workshop on Artificial Intelligence for IT Operations, AIOps 2021, 3rd Workshop on Smart Data Integration and Processing, STRAPS 2021, International Workshop on AI-enabled Process Automation, AI-PA 2021 and Scientific Satellite Events held in conjunction with 19th International Conference on Service-Oriented Computing, ICSOC 2021 - Virtual, Online
Duration: 22 Nov 202125 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13236 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshop on Artificial Intelligence for IT Operations, AIOps 2021, 3rd Workshop on Smart Data Integration and Processing, STRAPS 2021, International Workshop on AI-enabled Process Automation, AI-PA 2021 and Scientific Satellite Events held in conjunction with 19th International Conference on Service-Oriented Computing, ICSOC 2021
CityVirtual, Online
Period22/11/2125/11/21

Keywords

  • Anomaly detection
  • Cloud computing
  • Hypervisor
  • VMM

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